In one aspect, computer-implemented method may include receiving, from a cloud-based computing system, one or more machine learning model parameters that are configured to enable predicting a remaining useful life of each cell of a battery pack of a vehicle. The method may include loading, into memory of a processing device at the vehicle, the one or more machine learning model parameters, receiving data comprising one or more measurements and one or more user battery usage profiles, and based on the data, executing a trained machine learning model with the one or more parameters to input the data and to output the remaining useful life of each cell of the battery pack.

In one aspect, computer-implemented method may include receiving, from a cloud-based computing system, one or more machine learning model parameters that are configured to enable predicting a remaining useful life of each cell of a battery pack of a vehicle. The method may include loading, into memory of a processing device at the vehicle, the one or more machine learning model parameters, receiving data comprising one or more measurements and one or more user battery usage profiles, and based on the data, executing a trained machine learning model with the one or more parameters to input the data and to output the remaining useful life of each cell of the battery pack.

Systems, methods, and storage media for generating a predicted discharge profile of a vehicle battery pack are disclosed. A method includes receiving, by a processing device, data pertaining to cells within a battery pack installed in each vehicle of a fleet of vehicles operating under a plurality of conditions, the data received from at least one of each vehicle in the fleet of vehicles, providing, by the processing device, the data to a machine learning server, directing, by the processing device, the machine learning server to generate a predictive model, the predictive model based on machine learning of the data, generating, by the processing device, the predicted discharge profile of the vehicle battery pack from the predictive model, and providing the discharge profile to an external device.

Systems, methods, and storage media for generating a predicted discharge profile of a vehicle battery pack are disclosed. A method includes receiving, by a processing device, data pertaining to cells within a battery pack installed in each vehicle of a fleet of vehicles operating under a plurality of conditions, the data received from at least one of each vehicle in the fleet of vehicles, providing, by the processing device, the data to a machine learning server, directing, by the processing device, the machine learning server to generate a predictive model, the predictive model based on machine learning of the data, generating, by the processing device, the predicted discharge profile of the vehicle battery pack from the predictive model, and providing the discharge profile to an external device.

A method for detecting a lithium plating state of a battery includes regularly collecting a voltage of a battery after the end of charging at a preset time interval after the battery is in an idle state, and associatively storing the collected voltage and a collection time as voltage data; constructing a time-differential voltage curve in a voltage-time coordinate system according to the voltage data; detecting whether a characteristic peak voltage exists in the time-differential voltage curve; and sending a warning message when detecting that the characteristic peak voltage exists in the time-differential voltage curve.

The present invention discloses a method and system for charging rechargeable battery cells in series. When the voltage of a specific battery cell is too high, discharge the specific battery cell, and at the same time let other battery cells with lower voltage continue to charge, so that each battery cell in series can be charged to almost the same level. This invention designs in a “Total voltage follow-up charging method”, a Battery Manage System (BMS) detects total voltage of the series-connected battery in real-time and modifies an “equalizing trigger voltage”, as the total voltage drifts the equaling function still works well.

The present invention discloses a method and system for charging rechargeable battery cells in series. When the voltage of a specific battery cell is too high, discharge the specific battery cell, and at the same time let other battery cells with lower voltage continue to charge, so that each battery cell in series can be charged to almost the same level. This invention designs in a “Total voltage follow-up charging method”, a Battery Manage System (BMS) detects total voltage of the series-connected battery in real-time and modifies an “equalizing trigger voltage”, as the total voltage drifts the equaling function still works well.

A cell sampling circuit includes a plurality of target units sequentially connected in a series connection in a daisy-chain communication manner and one or more transformer units each connected between two successive target units of the plurality of target units. Each of the target units is configured to acquire an impedance of at least one transformer unit connected to the target unit, and judge, based on the acquired impedance, whether to perform circuit abnormality early warning.

A cell sampling circuit includes a plurality of target units sequentially connected in a series connection in a daisy-chain communication manner and one or more transformer units each connected between two successive target units of the plurality of target units. Each of the target units is configured to acquire an impedance of at least one transformer unit connected to the target unit, and judge, based on the acquired impedance, whether to perform circuit abnormality early warning.

A battery monitoring system includes a data receiver configured to receive battery information data and vehicle information data from a data collecting device connected to a vehicle, a battery management score calculator configured to calculate, based on the battery information data and the vehicle information data, factors affecting battery degradation among a charging habit, a driving habit, and a parking habit of a user, calculate, based on the factors, a battery management score, and store the battery management score in a database, and an information transmitter configured to transmit the battery management score to a terminal.